Search Results (1,205)

Microwave-assisted heating (MWH) has established itself as a transformative and energy-efficient paradigm for advanced materials processing. This review provides a comprehensive overview of the advances achieved at the CNR-SCITEC laboratories in Genoa. In this context, a customized microwave platform has been strategically employed for the synthesis, sintering, foaming, and melting of diverse inorganic, organic, and hybrid systems. The spectrum of materials investigated includes superconducting magnesium diboride (MgB₂), hydroxyapatite-based scaffolds, polyethylene components obtained via microwave-assisted rotational molding, cork-based sound-adsorbing composites, recycled expanded polystyrene (rEPS) panels, and polyvinylidene fluoride (PVDF) piezoelectric films. Across the case studies, MWH demonstrated a superior capacity for reducing energy consumption and processing times while maintaining—or even enhancing—the target functional properties. Furthermore, this work evaluates the technological maturity and emerging market opportunities of microwave-based processing, positioning it as a key and sustainable platform for next-generation materials development. Full article

Sugarcane (Saccharum spp. L.) is a globally vital sugar and energy crop whose genetic improvement has been constrained by its complex polyploid–allopolyploid genome. To address this limitation, we developed a practical, high-throughput single-nucleotide polymorphism (SNP) genotyping system. Using specific-locus amplified fragment sequencing (SLAF-seq) on 107 diverse accessions, we identified 2,420,550 high-quality SNPs anchored to the Saccharum officinarum LA-Purple genome. Stringent filtering yielded 55,750 SNPs for population analysis, which revealed three distinct genetic groups consistent with breeding history and adaptation. From these resources, 329 SNPs were converted into PCR-based ligase detection reaction (PCR-LDR) markers, resulting in a validated panel of 177 highly reliable SNPs (151 core and 26 extended) organized into an efficient multiplex typing system. The panel exhibited exceptional discriminatory power, successfully distinguishing all 303 tested sugarcane varieties and clearly resolving 186 individuals from three segregated hybrid populations. Compared to existing SSR and SNaPshot platforms, this SNP system offers superior experimental reproducibility, enhanced varietal clustering, and broader genome coverage. This work provides a robust, efficient genotyping tool to advance sugarcane variety identification, germplasm management, pedigree analysis, and marker-assisted breeding, with potential applicability to other complex polyploid crops. Full article

Accurate normalization of RT-qPCR data requires selecting stable internal control genes, particularly in models characterized by dynamic metabolic transitions, such as 3T3-L1 adipocytes. The current study compares the expression stability of nine widely used housekeeping genes (HKGs) (peptidylprolyl isomerase A (Ppia), glyceraldehyde-3-phosphate dehydrogenase (Gapdh), beta-2 microglobulin (B2M), ribosomal protein, large, P0 (36b4), hydroxymethylbilane synthase (Hmbs), hypoxanthine guanine phosphoribosyl transferase (Hprt), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide (Ywhaz), 18S ribosomal RNA (18S), and β-actin (Actb)) across key stages of differentiation (days 0, 9, and 18) and under treatments with palmitic acid and docosahexaenoic acid. Stability was assessed using four classical algorithms—geNorm, NormFinder, BestKeeper, and RefFinder—supplemented by the ΔCt method, conventional statistical testing, correlation, and regression analysis relative to two target genes, fatty acid-binding protein 4 (Fabp4) and sterol regulatory element binding transcription factor 1 (Srebf1). The obtained data indicate that no single HKG remains universally stable across these experimental conditions, and the expression of traditionally used reference genes (Gapdh, Actb, Hprt, 18S) is highly influenced by both the stage of adipogenesis and exposure to lipid-modulating factors. In contrast, Ppia, 36b4, and B2M—despite some of them being underestimated in use as references—consistently display the lowest variability across most analytical tools, forming a reliable and functionally diverse normalization panel. It should be noted that our initial stability assessment revealed apparent discrepancies among mathematical evaluation methods, emphasizing the need for a holistic, multiple-level approach strategy. The applied combination of algorithmic and statistical methods provides a more rigorous and objective framework for assessing the stability of reference genes, which is highly recommended in such a complex adipocyte-based model. Full article

Optimizing photovoltaic (PV) installations requires precise understanding of the annual energy yield, which depends heavily on geographical location, panel technology, tilt, and azimuth. This study establishes the framework for a “European Photovoltaic Atlas”. In this pilot phase, the dynamic tool is applied to representative European climatic zones to compare diverse latitudes and technologies. Consequently, we aim to create a robust database and interactive visualization tool that allows users to analyze technology-specific yields based on variable orientation parameters. The study employs a large-scale simulation campaign using EnergyPlus coupled with a PVWatts model. Two photovoltaic technologies (PERC and TOPCon monocrystalline) have been simulated in seven European reference cities: Naples, Madrid, Berlin, Paris, London, Stockholm, and Warsaw. For each city and technology, simulations have been performed for a complete grid of orientations. The tilt was varied from 0° to 90° in 5° increments, and the azimuth was varied from 0° to 360° in 5° increments. All panels have been simulated at a height of 15 m to represent typical rooftop installations. The main result is a comprehensive database that links location, technology, tilt, azimuth, and normalized annual energy yield. This database feeds an interactive application developed in Python. This tool generates 2D heatmaps showing the surface orientation factor of any selected city–technology pair, 3D surface plots comparing performance across multiple technologies or locations simultaneously, and 2D charts estimating hourly annual productivity by varying technology efficiency values. The “Photovoltaic Atlas” serves as a practical decision support tool for architects and engineers by enabling the rapid optimization of photovoltaic systems and clearly illustrating performance in the European context. Full article

Purpose: To develop a transparent and adaptable methodological framework for the analysis of microsatellite status using Next Generation Sequencing (NGS), addressing current limitations in clinical implementation. Methods: Microsatellite status was assessed using NGS with a custom-designed panel. The approach was validated against polymerase chain reaction (PCR) and immunohistochemistry (IHC) results in a cohort of 32 patients with various tumor entities. A Python-based analysis pipeline was developed to process raw sequencing data and quantify mutational burden within microsatellite regions. Results: The proposed method demonstrated 100% concordance with PCR and 90.32% concordance with IHC results. The framework enabled quantitative assessment of microsatellite instability. Conclusions: This proof-of-concept study demonstrates reliable determination of microsatellite status. The transparent and panel-adaptable framework offers flexibility for clinical implementation and provides a robust foundation for further validation in larger cohorts and across diverse tumor entities. Full article

While Escherichia coli can be found in the bladders of females without lower urinary tract symptoms, its presence is often associated with urinary tract infections (UTIs). The genomic plasticity of E. coli, including urogenital strains, is largely shaped by the integration of prophages. Although genomic and metagenomic analyses of urinary E. coli and the urinary microbiome suggest that prophages are abundant, many represent uncharacterized species. Sequence analysis suggests that these prophages represent temperate phages. This study aimed to fill this gap, isolating and characterizing temperate phages from urinary E. coli strains. We assessed phage host range across a panel of urinary isolates, providing a critical first step for future work investigating their putative role in shaping E. coli populations within the urinary community. In total, 20 temperate urinary phages were evaluated. Phage morphology and genic content of these phages were determined via transmission electron microscopy (TEM) and whole-genome sequencing, respectively. Together, these analyses provide insight into the diversity, infectivity, and genomic composition of temperate coliphages from the female urinary tract. Full article

Background: Streptococcus pneumoniae (Spn) is a leading bacterial pathogen responsible for severe invasive diseases, including meningitis, sepsis, and pneumonia. Current pneumococcal vaccines, which are all based on capsular polysaccharide antigens, provide limited protection and are further compromised by post-vaccination serotype replacement. Pneumococcal surface protein A (PspA), a highly conserved virulence factor expressed across diverse serotypes, has emerged as a promising candidate antigen for novel protein-based vaccines. However, progress in this field has been hindered by the absence of standardized in vitro functional antibody assays. Methods: This study established a robust functional antibody detection method for PspA-based protein vaccines by modifying the conventional multiplex opsonophagocytic killing assay (MOPA), originally designed for polysaccharide-based vaccines. Using polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) typing, a target strain panel was selected and developed to include representative strains from PspA Family 1-Clade 2 and Family 2-Clades 3 and 4. The MOPA protocol was optimized by extending the phagocytic reaction time to enhance sensitivity. Specificity was confirmed through recombinant PspA competitive inhibition assays. Results: The assay demonstrated high linearity (R² ≥ 0.98) between opsonophagocytic index (OI) and serum dilution, along with acceptable repeatability (CV ≤ 30%) and intermediate precision (CV ≤ 50%). Both preclinical and clinical serum samples exhibited potent bactericidal activity against diverse PspA families, independent of capsule type. Conclusions: This study provided a standardized framework to support the development and regulatory assessment of protein-based pneumococcal vaccines. Full article

Introduction: Epilepsy syndromes show marked clinical and genetic heterogeneity, with numerous functionally diverse genes involved in their etiology. Next-generation sequencing (NGS) has facilitated the identification of many monogenic epilepsy syndromes and enables earlier, more accurate diagnosis in pediatric patients. Materials and Methods: This study analyzes the molecular profiles of 87 pediatric patients with various forms of epilepsy in whom pathogenic or likely pathogenic variants were identified. Next-generation sequencing (NGS) using multi-gene epilepsy panels or whole-exome sequencing (WES) was performed. Results: A total of 88 pathogenic or likely pathogenic variants were detected in 48 epilepsy-related genes; 30 variants occurred de novo. SCN1A and KCNQ2 were the most frequent contributors (12.6% and 9.2%, respectively). The highest percentage of positive diagnoses (48%) was observed in patients with developmental and epileptic encephalopathy (DEE), with variants identified in genes including ALG13, ATP1A2, CACNA1A, CDKL5, CHD2, GABRG2, ITPA, KCNQ2, PCDH19, SCN1A, SCN2A, SCN3A, SCN8A, SMC1A, SPTAN1, STXBP1, and UBA5. Pathogenic variants in ANKRD11 were found in four patients with KBG syndrome, while other genes appeared sporadically. Conclusions: Targeted massively parallel sequencing is an effective diagnostic tool for pediatric epilepsy. The presence of numerous single-case findings highlights the high genetic heterogeneity of epilepsy. This approach enabled more precise diagnoses that would not have been achieved through clinical evaluation alone, underscoring the importance of genetic testing for prognosis and treatment planning in pediatric patients with unexplained epilepsy. Full article

Green space equity is increasingly recognized as a critical environmental condition for healthy aging, yet existing research often overlooks how different green space attributes—accessibility and diversity—are associated with distinct dimensions of older adults’ health. Limited attention has been paid to their nonlinear threshold effects or to the social pathways through which green spaces influence health outcomes. Using the United States county-level panel data from 2020 to 2023, this study integrates fixed-effects models, Extreme Gradient Boosting (XGBoost), and mediation analysis to examine the associations between green accessibility measured by the Two-Step Floating Catchment Area (2SFCA) method, and green diversity measured by the Shannon Index, on the general, physical, and mental health of older adults. Findings indicate that (1) higher green accessibility is associated with better general health, whereas green diversity shows a stronger association with physical health, reflecting its link to more heterogeneous ecosystem service environments. (2) Green accessibility demonstrates the threshold effect, in which the strength of association with health becomes steeper once accessibility approaches higher levels. (3) Green space equity is linked to health partly through social structures. Education clustering and marital stability mediate the associations with general health, while mental health appears to depend more on the social interaction opportunities embedded within green environments than on their physical attributes alone. The study proposes an integrated “physical environment–social structure–health outcome” framework and a threshold-oriented spatial intervention strategy, highlighting the need to prioritize improvements in green accessibility in underserved areas and prioritizing green diversity and age-friendly social functions where accessibility is already high. These findings offer evidence for designing inclusive, health-oriented urban environments for aging populations. Full article

A major challenge for food-derived bio-nanomaterials is achieving consistent and predictable functional properties to ensure their quality. Ginger-derived exosome-like nanovesicles (GELNs) serve as an ideal model for this challenge, yet the impact of ginger geographical origin on GELNs remains unknown. This study aims to establish a quality control framework for food-derived bio-nanomaterials. GELNs were comprehensively analyzed. Untargeted metabolomics identified differential metabolites, which were then screened for correlation with antioxidant capacity. Machine learning was employed to pinpoint potential quality markers, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis highlighted key metabolic pathways. Significant variations in physicochemical properties and bioactivities were observed. We identified 190 differential compounds and established a panel of 6 potential quality markers. Enrichment analysis revealed eight key pathways, with “microbial metabolism in diverse environments” and “galactose metabolism” being most prominent. The quality marker mollicellin I (derived from Chaetomium brasiliense) provided empirical support linking GELNs quality to geography-specific microbiota. Our findings provide evidence that the geographic origin of raw materials is a primary determinant of GELNs quality, based on a systematic analysis of their chemical and functional properties. We develop a transferable quality control framework, laying the groundwork for producing superior natural food-derived nanomaterials. Full article

Background/Objectives: While tick-borne encephalitis virus (TBEV) is genetically relatively conserved, the significant antigenic divergence between its main circulating subtypes hinders the development of broadly effective antiviral treatments and vaccines. Current inactivated TBEV vaccines offer limited cross-protection against heterologous strains, as evidenced by cases among vaccinated individuals in endemic regions. The aim of this study was to design a candidate mRNA vaccine and evaluate the breadth of protective immunity it elicits. Methods: Ten candidate mRNA-PrM/E-LNP vaccines were comparatively evaluated for immunogenicity and protective efficacy in BALB/c mice. Immunogenicity was assessed by measuring antigen-specific IgG titers via ELISA and neutralizing antibody titers against a panel of TBEV strains using a virus-neutralization test. Protective efficiency was determined in a lethal challenge model, where immunized mice were challenged with one of seven distinct TBEV strains. Results: Vaccination with all tested mRNA-PrM/E-LNP candidates conferred 100% survival in mice following a lethal challenge with each of the seven TBEV strains (100 LD₅₀). The construct mRNA-PrM/E—Krasny Yar-8 demonstrated the highest immunogenicity, inducing antigen-specific antibodies with a geometric mean titer (GMT) of 1:6625, as well as the broadest virus-neutralizing activity against both homologous and heterologous TBEV strains in vitro. Conclusions: The mRNA platform represents a promising strategy for developing TBEV vaccines, demonstrating high immunogenicity and cross-protective efficacy against diverse viral strains. Full article

Solar energy is a widely available renewable source suitable for diverse applications, including residential, industrial and aerospace sectors. To maximize energy capture, solar tracking systems adjust panels to maintain perpendicular alignment with sunlight. Various tracking techniques are employed to adjust these trackers, such as sensors, predefined algorithms, deep learning, and image-processing techniques. Image processing-based trackers have gained prominence for their precision and accuracy. This approach uses cameras as sensors to capture real-time sky images and analyze them to detect the sun and its coordinates, orienting solar panels toward its center. This technology can be integrated with other techniques to enhance energy output with high accuracy, minimal tracking error, and low maintenance requirements. This review examines computer vision methods used in solar tracking systems, synthesizing findings from 26 studies published between 2009 and 2024. The paper discusses main system components, methods utilized, and results obtained. Findings demonstrate that the robustness and accuracy of these tracking systems have increased compared to other tracking systems, while tracking error has decreased. Full article

This study examines the relationship between publicly traded Thai companies’ ESG performance and value as well as how board structures moderate this. In the Thai context, there is a limited number of empirical studies that employ the board of directors’ structure as a moderating variable, despite the importance of the board’s role in corporate management. This study aims to address this research gap. A panel GMM regression model is employed to address endogeneity issues, and our sample consists of 94 Thai listed companies with available ESG data from 2019 to 2023, resulting in 470 firm-year observations. The results demonstrate positive direct impact of ESG score on corporate value. In addition, board independence is positively significant and relates to company value. However, this research found negative moderating effect of board independence on the relationship between ESG score and corporate value. Furthermore, the empirical results indicate that board size does not have a significant direct and moderate impact on corporate value. Moreover, firm size and leverage are not related to corporate value. The results confirm the agency theory and stakeholder theory. Based on the findings, company executives should integrate ESG practices into their strategic plans. Moreover, regulatory authorities should promote expertise diversity and independence within the board and promote ESG standards and disclosure, as well as offer tax incentives for companies with outstanding ESG. This would enable investors to consider ESG performance in their decision-making. This study represents a new contribution to literature, especially in the context of emerging markets. Full article

Three new pyrrole alkaloids, streptopyrroles D–F (1–3), along with four known analogs (4–7) were isolated from Sea Anemone-Associated Streptomyces sp. S1502 via an OSMAC (One Strain Many Compounds)-based strategy. Their structures were elucidated through comprehensive spectroscopic analyses, including HRESIMS and 1D/2D NMR experiments (COSY, HSQC, and HMBC), and further confirmed by X-ray crystallography. Biological evaluation identified streptopyrrole (4) as an anti-MRSA (methicillin-resistant Staphylococcus aureus) agent, while 4 and 6 displayed broad-spectrum cytotoxicity and good selectivity against a panel of human cancer cell lines. Notably, 4 and 6 showed particularly potent activity against the lung cancer cell lines H1299, SW1573, and A549, with IC₅₀ values ranging from 5.43 to 16.24 μM. Further mechanistic investigation revealed that both compounds suppress the proliferation of lung cancer cells by inducing cell cycle arrest at the G₀/G₁ phase and impair metastatic potential by inhibiting migration and invasion. These findings not only expand the structural diversity of marine-derived pyrrole alkaloids but also reveal the anticancer mechanisms of 4 and 6, highlighting their promise as active candidates for further antitumor drug development, particularly in lung cancer. Full article

This study provides new evidence on how production digitalization investment affects firm financial performance across diverse European regions. A panel of 14,935 firm-year observations from 30 countries (2012–2022), including a focused Baltic subsample, is used alongside a refined digital capital intensity metric based on depreciated plant and machinery value. The results indicate a positive association between digital investment and operating revenue across Europe, with significantly stronger effects observed in the Baltic region. Interaction models reveal higher marginal returns for Baltic firms, suggesting that digital capital delivers amplified value in economies with lower digital saturation but greater absorptive urgency. Employee-related costs consistently predict revenue outcomes, underscoring their role in translating digital assets into performance. Intangible fixed assets exhibit a positive impact in Baltic labor-scale models but weaker effects elsewhere, indicating that institutional maturity mediates knowledge capital productivity. Implications: (1) digital investment yields asymmetric returns; (2) workforce investment enhances digital ROI; and (3) policy should prioritize organizational readiness alongside infrastructure. This study contributes by introducing a replicable proxy for production-level digitalization and by providing rare comparative evidence on digital returns in transitional versus mature European economies. Full article